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Integrating Green Infrastructure With AI-Driven Dynamic Workload Optimization: Focus on Network and Chip Design
Abstract
The integration of green infrastructure with AI-driven dynamic workload optimization offers a transformative approach to sustainable technology design, specifically within the fields of network and chip architecture. As the demand for energy-efficient systems continues to rise, this chapter explores the potential of leveraging artificial intelligence (AI) to dynamically optimize workloads, reducing power consumption and enhancing system performance. Through a detailed analysis of network and chip design principles, we investigate how AI can autonomously manage energy flows, predict workload variations, and redistribute tasks to improve efficiency. The chapter also highlights the role of green infrastructure in reducing the environmental footprint of modern computing systems, emphasizing the need for sustainable approaches in both hardware and software development. By integrating AI-driven optimization techniques with environmentally-conscious infrastructure design, this research aims to pave the way for next-generation, low-power, high-performance systems that balance performance with sustainability.
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